Decentralized Privacy-Preserving Proximity Tracing

This repository contains a proposal for a secure and privacy-preserving decentralized privacy-preserving proximity tracing system. Its goal is to simplify and accelerate the process of identifying people who have been in contact with an infected person, thus providing a technological foundation to help slow the spread of the SARS-CoV-2 virus. The system aims to minimise privacy and security risks for individuals and communities and guarantee the highest level of data protection.

By publishing this document we seek feedback from a broad audience on the high-level design, its security and privacy properties, and the functionality it offers; so that further protection mechanisms can be added if weaknesses are identified. This document is accompanied by an overview of the Data Protection compliance of the design.

The following people are behind this design:

EPFL: Prof. Carmela Troncoso, Prof. Mathias Payer, Prof. Jean-Pierre Hubaux, Prof. Marcel Salathé, Prof. James Larus, Prof. Edouard Bugnion, Dr. Wouter Lueks, Theresa Stadler, Dr. Apostolos Pyrgelis, Dr. Daniele Antonioli, Ludovic Barman, Sylvain Chatel
ETHZ: Prof. Kenneth Paterson, Prof. Srdjan Capkun, Prof. David Basin, Dennis Jackson
KU Leuven: Prof. Bart Preneel, Prof. Nigel Smart, Dr. Dave Singelee, Dr. Aysajan Abidin
TU Delft: Prof. Seda Guerses
University College London: Dr. Michael Veale
CISPA: Prof. Cas Cremers
University of Oxford: Dr. Reuben Binns